Abstract
We present our third and final generation joint P and S global adjoint tomography (GLAD) model, GLAD-M35, and quantify its uncertainty based on a low-rank approximation of the inverse Hessian. Starting from our second-generation model, GLAD-M25, we added 680 new earthquakes to the database for a total of 2160 events. New P-wave categories are included to compensate for the imbalance between P- and S-wave measurements, and we enhanced the window selection algorithm to include more major-arc phases, providing better constraints on the structure of the deep mantle and more than doubling the number of measurement windows to 40 million. Two stages of a Broyden–Fletcher–Goldfarb–Shanno (BFGS) quasi-Newton inversion were performed, each comprising five iterations. With this BFGS update history, we determine the model’s standard deviation and resolution length through randomized singular value decomposition.
| Original language | English |
|---|---|
| Pages (from-to) | 478-502 |
| Number of pages | 25 |
| Journal | Geophysical Journal International |
| Volume | 239 |
| Issue number | 1 |
| DOIs | |
| State | Published - Oct 1 2024 |
Funding
This research used resources from the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under contract DE-AC05-00OR22725. Additional computational resources were provided by the Princeton Institute for Computational Science & Engineering (PICSciE). We acknowledge IRIS (iris.edu) and ORFEUS (orfeus-eu.org) for providing the data used in this study. We thank Stephen Beller for contributing his Laplacian kernel smoothing software and for discussing the implementation of the approximate Hessian. Comments and suggestions by two reviewers and editor Andrew Valentine helped improve an earlier version of the paper. We thank the EarthScope Earth Model Collaboration project (Trabant et al. 2012, Hutko et al. 2017, IRIS DMC 2011) for hosting a wide range of earth models and the SubMachine project (Hosseini et al. 2018) for providing a web-based visualization tool for earth models. We thank Manochehr Bahavar for creating the EarthScope Earth Model Collaboration webpage for GLAD-M35 (Cui et al. 2024). The open-source spectral-element software package SPECFEM3D GLOBE and the seismic measurement software package FLEXWIN used for this paper are freely available via specfem.org. This research was supported by NSF grants 1945565, 2000801 and 2244661. This research used resources from the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under contract DE-AC05-00OR22725. Additional computational resources were provided by the Princeton Institute for Computational Science & Engineering (PICSciE). We acknowledge IRIS ( iris.edu ) and ORFEUS ( orfeus-eu.org ) for providing the data used in this study. We thank Stephen Beller for contributing his Laplacian kernel smoothing software and for discussing the implementation of the approximate Hessian. Comments and suggestions by two reviewers and editor Andrew Valentine helped improve an earlier version of the paper. We thank the EarthScope Earth Model Collaboration project (Trabant et al. , Hutko et al. , IRIS DMC ) for hosting a wide range of earth models and the SubMachine project (Hosseini et al. ) for providing a web-based visualization tool for earth models. We thank Manochehr Bahavar for creating the EarthScope Earth Model Collaboration webpage for GLAD-M35 (Cui et al. ). The open-source spectral-element software package SPECFEM3D_GLOBE and the seismic measurement software package FLEXWIN used for this paper are freely available via specfem.org . This research was supported by NSF grants 1945565, 2000801 and 2244661.
Keywords
- Computational seismology
- Seismic tomography
- Wave propagation
- Waveform inversion